EAGER: BullyBlocker - Identifying Cyberbullying in Social Networking Sites

网络欺凌是青少年最常见的网络风险，但大多数在网络上受到欺凌的年轻人在发生网络欺凌时不会告诉父母。BullyBlocker项目的目标是促进人们对如何在社交网站上有效识别网络欺凌，特别是网络欺凌，以及更广泛的行为问题的理解。这个跨学科的项目整合了计算机科学的进步和网络欺凌心理学研究的主要发现，以(I)设计和实施识别社交网络平台上的网络欺凌的模型，以及(Ii)研究基于这些模型的自动化工具的使用模式，以及它们对设计和测试关于网络欺凌风险因素的新假设的效用。这个项目的智力价值来自于它将计算机和心理科学协同整合起来，以解决一个对青少年、他们的家庭和社会产生负面影响的社会问题。该项目利用对网络欺凌风险因素的心理学研究和计算机科学的进步，来开发自动识别模型，并将这些模型整合到一个应用程序(BullyBlocker)中，通知父母他们青少年遭受网络欺凌的风险。该项目还需要设计机制，为父母和受害者生成定制的反欺凌资源，调查应用程序的使用模式和父母对自动识别工具的态度，使用自动工具(如BullyBlocker)设计和测试关于网络欺凌的新假设，以及为研究生和本科生提供科学支撑以发展为公认的跨学科学者的独特培训机会。

Cyberbullying is the most common online risk for adolescents, yet the majority of young people who are bullied online do not tell their parents when it occurs. The goal of the BullyBlocker project is to advance the understanding of how cyberbullying, in particular, and behavioral issues, more broadly, can be effectively identified on social networking sites. This interdisciplinary project integrates advances in computer sciences and key findings from psychological research on cyberbullying to (i) design and implement models for identifying cyberbullying on social networking platforms, and (ii) study usage patterns of automated tools based on these models and their utility for devising and testing new hypotheses about cyberbullying risk factors. The intellectual merit of this project stems from its synergistic integration of computer and psychological science to address a social problem that negatively impacts adolescents, their families, and society. The project draws on psychological research on cyberbullying risk factors and advances in computer science to enable the development of automated identification models and the integration of these models into an app (BullyBlocker) that notifies parents about their adolescents' risk of cyberbullying. The project also entails the design of mechanisms to generate customized anti-bullying resources for parents and victims, investigation of app usage patterns and parents' attitudes towards automated identification tools, the use of automated tools such as BullyBlocker to devise and test new hypotheses about cyberbullying, and a unique training opportunity that provides graduate and undergraduate students with the scientific scaffolding to develop into recognized interdisciplinary scholars.